Validation of the Delirium Observation Screening Scale in long‐term care facilities in Flanders
Bibliographic record
Abstract
AIM: The aim of this study was to validate the Delirium Observation Screening Scale (DOSS) in a population of long-term care facility (LTCF) residents in Flanders. Currently there is no validated screening tool for delirium available for the population in this setting in Flanders. METHODS: A multisite, cross-sectional study was conducted in six LTCFs. A total of 338 residents aged 65 years and older were included. Sociodemographic and clinical data, including data from the Montreal Cognitive Assessment (MoCA), Confusion Assessment Method (CAM) and DOSS, were obtained by three trained nurse researchers. For the DOSS, internal consistency was determined, and inter-rater reliability was calculated. To validate the DOSS, the sensitivity, specificity, and positive and negative predictive value of the DOSS relative to the CAM were determined through receiver operating characteristic analysis. This article adheres to the Strengthening the Reporting of Observational Studies (STROBE) checklist for observational research. RESULTS: For 338 residents, delirium assessments were completed during an early or late shift. The prevalence of delirium was 14.2% as measured with the DOSS. The reliability (α) for the CAM and DOSS was assessed, as was the inter-rater reliability (κ) and the area under the curve. The sensitivity and specificity for a cut-off value of 3 on the DOSS by Youden's index were very high, as was the negative predictive value. The positive predictive value was good. CONCLUSIONS: This study showed that the DOSS is a reliable and valid instrument to screen for delirium in LTCF residents in Flanders. Geriatr Gerontol Int 2024; 24: 619-625.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".